title: Compensating for literature annotation bias when predicting novel drug-disease relationships through Medical Subject Heading Over-representation Profile (MeSHOP) similarity.
abstract: BACKGROUND
  Using annotations to the articles in MEDLINE®/PubMed®, over six thousand chemical compounds with pharmacological actions have been tracked since 1996. Medical Subject Heading Over-representation Profiles (MeSHOPs) quantitatively leverage the literature associated with biological entities such as diseases or drugs, providing the opportunity to reposition known compounds towards novel disease applications.
  
  
  METHODS
  A MeSHOP is constructed by counting the number of times each medical subject term is assigned to an entity-related research publication in the MEDLINE database and calculating the significance of the count by comparing against the count of the term in a background set of publications. Based on the expectation that drugs suitable for treatment of a disease (or disease symptom) will have similar annotation properties to the disease, we successfully predict drug-disease associations by comparing MeSHOPs of diseases and drugs.
  
  
  RESULTS
  The MeSHOP comparison approach delivers an 11% improvement over bibliometric baselines. However, novel drug-disease associations are observed to be biased towards drugs and diseases with more publications. To account for the annotation biases, a correction procedure is introduced and evaluated.
  
  
  CONCLUSIONS
  By explicitly accounting for the annotation bias, unexpectedly similar drug-disease pairs are highlighted as candidates for drug repositioning research. MeSHOPs are shown to provide a literature-supported perspective for discovery of new links between drugs and diseases based on pre-existing knowledge.
authors.affiliation: Centre for Molecular Medicine and Therapeutics at Child and Family Research Institute, University of British Columbia, Vancouver, BC, Canada.
authors.forename: Warren A
authors.initials: WA
authors.lastname: Cheung
authors.forename: B F Francis
authors.initials: BF
authors.lastname: Ouellette
authors.forename: Wyeth W
authors.initials: WW
authors.lastname: Wasserman
mesh_terms: D019295:Computational Biology; D016208:Databases, Factual; D004194:Disease; D015195:Drug Design; D058492:Drug Repositioning; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D016239:MEDLINE; D046650:Medical Subject Headings; D010506:Periodicals as Topic; D004364:Pharmaceutical Preparations / Q000737:chemistry*
chemical_list: D004364:Pharmaceutical Preparations